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Using Harris Corners for the Retrieval of Graphs in Historical Manuscripts

机译:使用Harris角检索历史手稿中的图形

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In recent years, several methods have been proposed for content-based retrieval from manuscripts, mostly based on character or word similarity. In this paper, we present a new segmentation-free method, called Harris Corner Matching (HCM), which accepts an arbitrary writing pattern as a model and allows to retrieve similar patterns from a possibly large database. Retrieval is performed in two steps. In the first step, candidate targets are determined by comparing configurations of interest points in query and data. In fact, interest points can be used as precomputed indices. In the second step, deviations between the interest point configurations of query and candidate target are used to warp the target, this way adapting it to the query. A final evaluation is obtained by template matching after binarization of query and target. The method has been evaluated for retrieval from historical Chinese and Sanskrit manuscripts and has shown good results.
机译:近年来,已经提出了几种方法来从手稿中进行基于内容的检索,这些方法大多基于字符或单词的相似性。在本文中,我们提出了一种称为Harris Corner Matching(HCM)的新的无分段方法,该方法接受任意书写模式作为模型,并允许从可能较大的数据库中检索相似的模式。检索过程分为两个步骤。第一步,通过比较查询和数据中兴趣点的配置来确定候选目标。实际上,兴趣点可以用作预先计算的指标。在第二步中,使用查询和候选目标的兴趣点配置之间的偏差来扭曲目标,从而使目标适应查询。在查询和目标进行二值化后,通过模板匹配获得最终评估结果。已对该方法进行了评估,可从历史汉语和梵文手稿中检索该方法,并显示出良好的效果。

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